Infimal convolution and AM-GM majorized total variation-based integrated approach for biosignal denoising-Reference-Cited by-同舟云学术

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Infimal convolution and AM-GM majorized total variation-based integrated approach for biosignal denoising

Published:2023-12-13 Issue: Volume: Page:
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Kumar Vinit,Muduli Priya Ranjan

Funder

Indian Space Research Organisation

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02902-7.pdf

Reference28 articles.

1. Sadad, T., Bukhari, S.A.C., Munir, A., Ghani, A., El-Sherbeeny, A.M., Rauf, H.T.: Detection of cardiovascular disease based on ppg signals using machine learning with cloud computing. Comput. Intell. Neurosci. 2022 (2022)

2. Tripathi, P.M., Kumar, A., Komaragiri, R., Kumar, M.: A review on computational methods for denoising and detecting ecg signals to detect cardiovascular diseases. Arch. Comput. Methods Eng., 1–40 (2021)

3. Allen, J.: Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3), 1 (2007)

4. Muduli, P.R., Kumar, V.: A proximity operator-based method for denoising biomedical measurements. Circuits, Syst. Signal Process., 1–25 (2023)

5. Singh, P., Pradhan, G., Shahnawazuddin, S.: Denoising of ecg signal by non-local estimation of approximation coefficients in DWT. Biocybern. Biomed. Eng. 37(3), 599–610 (2017)

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1. Wavelet-based Adaptive Boosting Method for Cuffless Blood Pressure Estimation on PYNQ-Z2;2024 International Conference on Signal Processing and Communications (SPCOM);2024-07-01

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